System and method for automated intelligent mobile application testing

ABSTRACT

A system for automated mobile application testing and activity monitoring where the mobile app runs on one of a plurality of available mobile devices running an operating system supported by the testing system. The automated testing system intelligently exercises each user interface element on each screen of the test mobile app for expected function, creating a graphical map of screen relationship and links in the process. Summary reports on user interface element function, mobile app usability and programming remediation hints on detailed pages may be displayed or sent to a client&#39;s software engineer task tracking package.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of, and priority to U.S. patentapplication Ser. No. 62/445,200, titled “SYSTEM AND METHOD FOR AUTOMATEDINTELLIGENT MOBILE APPLICATION TESTING” and filed on Jan. 11, 2017, theentire specification of which is incorporated herein by reference in itsentirety.

BACKGROUND

Field of the Art

The present invention is in the field of use of computer systems inbusiness information management, operations and predictive planning.Specifically, the use of an automated, intelligent system for mobileapplication testing.

Discussion of the State of the Art

Application testing has been a required task of software developmentsince the advent of the computer. As might be expected, the task beganas a fully manual endeavor with the process greatly exacerbated by theneed to introduce all patches into the code using manual punch cards ortapes and the paucity of computer time available to run those patchedprograms once submitted. The arrival of interactive modes of interactionwith the computer greatly streamlined application development includingthe testing and patching of applications in development. However, anapplication found to function correctly in-house at the developingcorporation often is shipped containing defects or “bugs,” some seriousincluding abnormal ending of the application or crashing of the entirecomputer system, that do not emerge until all aspects and usecombinations of the application's features are tested, a task that isresource prohibitive if done manually. Even the use of external “alpha”and “beta” testers may take a prohibitively long period of time and hasnot been shown to uncover even serious bugs with sufficient regularity.Recently, programs have been written with the sole purpose ofexhaustively exercising other programs, the applications in development.These testing system programs function continuously and extremelyrapidly, finally allowing such exhaustive exercise of all applicationfeatures in all plausible combinations and have greatly advanced thearea of application testing. Unfortunately, to date the vast majority ofthe test system programs are very ridged in what they do and are writtento test a single or extremely small subset of applications underdevelopment.

Nothing has increased the demand for new application development thanthe recent significant popularity of mobile devices including, but notlimited to smart phones and tablets. This demand shown left oldermethods of prerelease application testing sorely inadequate, even thenewer method of writing advanced but rigid single application testprogram systems.

What is needed is an automated mobile application test system that maybe given basic human interaction processes for most or all mobile apps,a small number of specific directives for a specific mobile app to betested and may then use techniques of artificial intelligence predictiveanalytic learning to exercise all interactive user interface elements ofapplications in such a fashion that the same system is generalized foruse in the exhaustive feature testing of all possible mobile apps.

SUMMARY

Accordingly, the inventor has developed a system for automatedintelligent mobile application testing which both accepts human trainingdirectives and uses predictive learning to exhaustively train bots andto exercise mobile application user interface (UI) elements and presentunexpected behavior events, usability predictions and improvementrecommendations to a service subscribing client.

According to one aspect, a system for automated intelligent mobileapplication testing comprising: a mobile application testing modulestored in a memory of and operating on a processor of a computing deviceand configured to: receive a mobile application for testing from anexternal source, install and run the mobile application onto a pluralityof mobile devices each connected to the mobile application testingmodule, exercise each user interface element on each screen of themobile application to predictively analyze correct behavior of thatelement using contextual cues found on each screen of the mobileapplication, previously learned behavioral expectations, and humanentered directives while simulating human interaction with thoseelements, create a relationship representation of all screens of themobile application, identify any deviation of behavior of user interfaceelements that make up the mobile application from predictively expectedbehavior for that element and receive, normalize and integratedirectives from a client's software engineer item tracking package.Further, a test results output module stored in a memory of andoperating on a processor of a computing device and configured to: formata plurality of results received from the mobile application testingmodule to best accomplish the intended function of those results isdisclosed.

According to another aspect, a system for automated intelligent mobileapplication testing has been reduced to practice. In the system, atleast one of the mobile devices runs the APPLE IOS™ operating system, atleast one of the mobile devices runs the GOOGLE ANDROID™ operatingsystem, at least one of the mobile devices runs the MICROSOFT WINDOWS™operating system, at least one of the test result output module formatsis a user interface element behavior summary report for elements of themobile application that was tested, at least one of the test resultoutput module formats is a detailed program and machine state report forhuman display, at least one of the test result output module formats isa report that provides metric derived usability scores and advice onremedy choices, at least one of the test result output module formats isto be sent to the client's software engineer item tracking package, and,at least one relationship representation of all screens of the mobileapplication is in the form of a multidimensional graph.

According to another aspect, a method for automated intelligent mobileapplication testing is disclosed using steps comprising: a) retrieving amobile application to be tested from an external source using a mobileapplication testing module stored in a memory of and operating on aprocessor of a computing device; b) installing and running the mobileapplication in the mobile application testing module using standardautomation application programming interfaces; c) exercising each userinterface element on each screen of the mobile application topredictively analyze correct behavior of that element using contextualcues found on each screen of the mobile application, previously learnedbehavioral expectations, and human entered directives while simulatinghuman interaction with those elements; d) creating a relationshiprepresentation of all screens of the mobile application using results ofnavigational element activation by the mobile application testingmodule; e) identifying any deviation of behavior of user interfaceelements that make up the mobile application from predictively expectedbehavior for that element using the mobile application testing module;f) receiving, normalizing and integrating directives from a client'ssoftware engineer item tracking package using a third-party softwareengineering service normalizer. g) formatting a plurality of resultsreceived from the mobile application testing module to best accomplishthe intended function of those results using a test results outputmodule stored in a memory of and operating on a processor of a computingdevice.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The accompanying drawings illustrate several aspects and, together withthe description, serve to explain the principles of the inventionaccording to the aspects. It will be appreciated by one skilled in theart that the particular arrangements illustrated in the drawings aremerely exemplary, and are not to be considered as limiting of the scopeof the invention or the claims herein in any way.

FIG. 1 is a diagram of an exemplary architecture of an intelligentmobile application testing system according to one aspect.

FIG. 2 is a method flow diagram of the function of the intelligentmobile application testing system according to one aspect.

FIG. 3 is a flow diagram of an exemplary function of the intelligentmobile application testing system for mapping the navigationalrelationships between pages of a mobile application.

FIG. 4 is an illustration of an analysis summary screen for a page of ahypothetical mobile application produced as part of the function of theintelligent mobile application testing system according to one aspect.

FIG. 5 is an example mobile application usability summary screenproduced as part of the function of the intelligent mobile applicationtesting system according to one aspect.

FIG. 6 is a block diagram illustrating an exemplary hardwarearchitecture of a computing device.

FIG. 7 is a block diagram illustrating an exemplary logical architecturefor a client device.

FIG. 8 is a block diagram illustrating an exemplary architecturalarrangement of clients, servers, and external services.

FIG. 9 is another block diagram illustrating an exemplary hardwarearchitecture of a computing device.

DETAILED DESCRIPTION

The inventor has conceived, and reduced to practice, a system forautomated intelligent mobile application testing.

One or more different aspects may be described in the presentapplication. Further, for one or more of the aspects described herein,numerous alternative arrangements may be described; it should beappreciated that these are presented for illustrative purposes only andare not limiting of the aspects contained herein or the claims presentedherein in any way. One or more of the arrangements may be widelyapplicable to numerous aspects, as may be readily apparent from thedisclosure. In general, arrangements are described in sufficient detailto enable those skilled in the art to practice one or more of theaspects, and it should be appreciated that other arrangements may beutilized and that structural, logical, software, electrical and otherchanges may be made without departing from the scope of the particularaspects. Particular features of one or more of the aspects describedherein may be described with reference to one or more particular aspectsor figures that form a part of the present disclosure, and in which areshown, by way of illustration, specific arrangements of one or more ofthe aspects. It should be appreciated, however, that such features arenot limited to usage in the one or more particular aspects or figureswith reference to which they are described. The present disclosure isneither a literal description of all arrangements of one or more of theaspects nor a listing of features of one or more of the aspects thatmust be present in all arrangements.

Headings of sections provided in this patent application and the titleof this patent application are for convenience only, and are not to betaken as limiting the disclosure in any way.

Devices that are in communication with each other need not be incontinuous communication with each other, unless expressly specifiedotherwise. In addition, devices that are in communication with eachother may communicate directly or indirectly through one or morecommunication means or intermediaries, logical or physical.

A description of an aspect with several components in communication witheach other does not imply that all such components are required. To thecontrary, a variety of optional components may be described toillustrate a wide variety of possible aspects and in order to more fullyillustrate one or more aspects. Similarly, although process steps,method steps, algorithms or the like may be described in a sequentialorder, such processes, methods and algorithms may generally beconfigured to work in alternate orders, unless specifically stated tothe contrary. In other words, any sequence or order of steps that may bedescribed in this patent application does not, in and of itself,indicate a requirement that the steps be performed in that order. Thesteps of described processes may be performed in any order practical.Further, some steps may be performed simultaneously despite beingdescribed or implied as occurring non-simultaneously (e.g., because onestep is described after the other step). Moreover, the illustration of aprocess by its depiction in a drawing does not imply that theillustrated process is exclusive of other variations and modificationsthereto, does not imply that the illustrated process or any of its stepsare necessary to one or more of the aspects, and does not imply that theillustrated process is preferred. Also, steps are generally describedonce per aspect, but this does not mean they must occur once, or thatthey may only occur once each time a process, method, or algorithm iscarried out or executed. Some steps may be omitted in some aspects orsome occurrences, or some steps may be executed more than once in agiven aspect or occurrence.

When a single device or article is described herein, it will be readilyapparent that more than one device or article may be used in place of asingle device or article. Similarly, where more than one device orarticle is described herein, it will be readily apparent that a singledevice or article may be used in place of the more than one device orarticle.

The functionality or the features of a device may be alternativelyembodied by one or more other devices that are not explicitly describedas having such functionality or features. Thus, other aspects need notinclude the device itself.

Techniques and mechanisms described or referenced herein will sometimesbe described in singular form for clarity. However, it should beappreciated that particular aspects may include multiple iterations of atechnique or multiple instantiations of a mechanism unless notedotherwise. Process descriptions or blocks in figures should beunderstood as representing modules, segments, or portions of code whichinclude one or more executable instructions for implementing specificlogical functions or steps in the process. Alternate implementations areincluded within the scope of various aspects in which, for example,functions may be executed out of order from that shown or discussed,including substantially concurrently or in reverse order, depending onthe functionality involved, as would be understood by those havingordinary skill in the art.

Conceptual Architecture

FIG. 1 is a diagram of an exemplary architecture 100 of an intelligentmobile application testing system according to one aspect. Mobileapplications (mobile apps) to be tested by the mobile applicationtesting system 110 may be run on a mobile app exercise module that is anintegral part of the mobile application testing system 111 but themobile app testing system is designed to allow these apps to be testedwhile running directly on any one of the available devices on which themobile app is designed to run, wherein the device being tested isconnected to, and directed by, the mobile application testing system 110operating as a controller to send operation request to the operatingsystem on the device for execution. The mobile app may be run on severaldifferent devices during the full testing process, which may testplatform specific performance characteristics such as GOOGLE ANDROID™vs. APPLE iOS™ vs. MICROSOFT WINDOWS™ mobile app versions for OSplatform specific programming deficiencies; multiple individual devicesrepresenting the same OS platform which may test OS version differencesin mobile app performance within the range of OS versions designated assupported by the mobile app being tested, for example iOS™ v.8 vs. v.9vs v.10 or ANDROID LOLLIPOP™ vs. MASHMALLOW™ vs. NOUGAT™, just to name afew likely examples from the larger set. Further, multiple mobiledevices of different supported types such as but not limited tosmartphones, tablets, or wearable devices, and from different vendorssuch as SAMSUNG™ smartphones, tablets, smartwatches, or virtual-reality(VR) headsets of different models, LG™ smartphones, tablets, orsmartwatches of different models and MOTOROLA™ smartphones orsmartwatches, among the many types and models known to those skilled inthe art, may be tested for differences in battery performancecharacteristics, graphics display failures, abnormal program ends andprogram progress halts, to name just a few possible mobile device modeleffects when using the mobile app undergoing analysis. General testsuites for a mobile app category such as appointment/schedule calendarmaintenance, virtual store front, social media gateway or mathematicallybased utility, just to name a few of many possibilities, may bepre-loaded by either a service administrator 133 or possibly the testclient using a menu or some other similar choice vehicle 132 known tothose skilled in the art, depending on the category into which themobile app to be tested belongs. Under other conditions, or given otherarrangements, the intelligent mobile application testing system mayindependently identify the category of the current test mobile app fromgraphic item content and action cues present on its screens. Thepre-load of general test suite directives may also cause the retrievalof information generated from past tests of similar software either bythe intelligent mobile application testing system or isolated stored andprovided by another, external source of such information 122, normalizedfor intelligent mobile application testing system use and locallystored, possibly both depending on the particular arrangement or usecase, from a mobile application exercise result data store 131. Thisinformation may be used to allow intelligent scrutiny of possible issuesoften present in the mobile app category, allow comparative usabilityscores to be assigned and to allow recommendations regarding the remedyof found deficiencies in the present mobile app under test to beproposed 121. The introduction into, and use of externally entered databy, is coordinated by an external directive module 116 duringintelligent mobile application testing system runs. The test of aparticular mobile app by the intelligent mobile application testingsystem may occur using any of four specialized test progression modes,although at any given instant of the test run, only one mode is active.

One such test mode is the discovery mode 113 which may be used primarilywhen the intelligent mobile application testing system encounters ascreen (or node) of the test mobile app of new or unknown functionality.When that condition is met, the software engineered mechanism that theintelligent mobile application testing system uses to traverse andexercise the screens and user interface (UI) elements of the test mobileapp, herein subsequently called a bot, assesses which UI components ofthe node may receive interactive user commands. For example, whichcomponents may respond to click or tap commands, which components mayreceive text input and which component or components may respond to morecomplex gestures such as swipes, flicks or pinches, just to name a fewof the many possible gestures available to a mobile app programmer. Foreach screen reference to each UI component, whether it responds directlyor possibly indirectly to some form of user interactive command, and itsposition on the screen is saved as part of the screen's noderepresentation internal to the intelligent mobile application testingsystem. The discovery mode assessment is partially done from standardautomation information, but standard information may be very limitedand, in some cases, may be entirely incorrect. Therefore, the inventionincludes heuristic programming algorithms that improve the accuracy ofdetermining what interaction commands are possible on the screen. Thisis generally based on such cues as the type of control(s) used toimplement the screen layout and content, and where on the screen tosimulate the interaction command although this list is not meant tolimit the types of interactions investigated by the invention. Forexample, sometimes a child control is reported to be unresponsive tointeraction commands but it has a parent or ancestor control that isregistered to respond to commands. Depending on the control types of theancestor and the parent, this may be a clue to not direct the command tothe ancestor control but to the child instead. The reason is based upona generally good guess that a child control has a higher z-order in theUI layout than the ancestor control. With a higher z-order, the childcontrol is on top of the ancestor. Therefore, scenarios where this isthe case are searched for, and if so the command is directed to thechild control even though the child control is reported to beunresponsive. This works because the ancestor control acts as asurrogate, and eventually receives and processes the command as long asit originated from within the x & y coordinate boundaries of the childcontrol and no other dependent child control has an even higher z-orderthan the target control. Of course, the previous is just one of multiplepossible examples of how the heuristic programming embodied in theinvention may allow greater interactive feature investigation by betterreproducing the actions a human user may perform during use than by justrandomly activating interactive elements, but the example should in noway be interpreted to limit the invention to identifying and correctlytraversing similar UI construction methods. Next the bot must decidewhat action or actions should be taken in order to exercise this portionof the application and/or discover additional functionality further intothe application. This decision may be aided using both intra-mobile apppredictive analytics provided by any existing test results 117 and anylearning allowed by the synthesis of those results into predictiveinsight 118, and any previous data retrieved on similar mobile apps 131and made available to the system 116. Once a set of actions are thusdetermined, the bot makes an assessment regarding success or failureregarding the actions taken. In discovery mode, success is achieved ifeach of the following hold true: the application did not crash; theapplication did not throw any exceptions; the application did not popupan error message to the UI; and, the screen has changed in some wayregarding either control composition or content when compared to thescreen present before any actions were taken. Otherwise it is recordedthat an application failure has occurred because of activation of thetested interactive component. This information is sent to the in the rawresult analyzer 117. Regardless of success or failure, the bot continuesin discovery mode which means it tries to continue to explore theapplication for pathways that have not yet been traversed.

A second test mode which may be used by aspects of the invention iscrawler mode 114. Crawler mode is invoked when the bot is traversingthrough a mobile app, and arrives at points in a mobile app where“forward exploration” is no longer possible. Therefore, the bot needs togo back to a previously known node in the mobile app in order to exploreother areas of the mobile app that have not been explored or have beenonly partially explored. Such reverse traversal may be as simple as thegoing to the previous screen using an available back button interactivecomponent, but in many cases traversal through nodes is not linear. So“going back” may not provide much utility. Also, some mobile apps do notsupport a “back” button at all. The system thus uses a statisticalweighting of all unexercised UI components under these circumstances.The system creates a ranking of the likelihood of how much functionalitysits behind each UI component to select a current node residentinteractive component with the highest probability of leading to apreviously mapped area of the mobile app. Once the target UI componentis chosen, then an application graph constructed by linking mobile appscreens together in a multidimensional graph represented relationship isused to determine the location of the test bot within the mobile appnode structure and the action steps needed to traverse known paths fromthe current node in the mobile app to a desired node where stillunexplored UI components may be accessed. Also, some paths within a testmobile app may be either transient or unidirectional, so the bot's firstattempt to determine the sequence of pathways may not always yield anexpected result. Therefore, the bot must recognize differences inapplication behavior from expected behavior, update the multidimensionalgraph of mobile app nodes accordingly, and devise a new strategy fornavigating through the application to the desired node. This processrepeats until the desired node is reached.

A third testing mode that may be used by aspects of the intelligentmobile application testing system, training mode 112 is invoked when oneor more nodes of the mobile app require specific text information suchas but not limited to a username, password, name of a particular objector name of a person of geographical location; a specific activationsequence of multiple interactive UI components of other set of actionsspecific to an individual or group known to those skilled in the art. Totraverse such specific types of interface elements where trial and errorusing random text entry or UI component activation will not result insuccessful traversal of a screen of the mobile app, the client may electto teach the intelligent mobile application testing system theinteraction information required using the client interface 132, whichis shown in this arrangement as being local to the test system forillustrative purposes, but may also be remote and connected over annetwork including a VPN tunneled on the internet 134. In action, the botmay be explicitly trained for an exact set of actions on a particularscreen, if desired. The client may use the client interface portal 132to identify the application screen on which it wants to train the bot byvisually selecting UI control components one by one, specifying thecorrect action to be performed by the test system at that control and/orentering any specific value to populate into the control in the cases oftext responses. Each screen is a unique node in the applicationmulti-dimensional graph. So the trained action and values is createdunder the graph point specified by the combination of the nodeidentifier plus the unique UI control component identifier. When the botis running and encounters a matching node and control(s), the trainedactions and values are used by the bot to traverse through that node ofthe application.

A last testing mode that may be used by the aspects of the intelligentmobile application testing system is a workflow mode 115. Two workflowtypes are modelled by the intelligent mobile application testing system.One type involves a series of actions that span multiple screens (nodes)to complete a task. A good example is the “check-out” process for astore front application. Typically, there are multiple screens, oneasking for shipping information, then one for billing information, onefor confirmation of items in the shopping basket, and then finally ascreen to review an order a final time in its final form and submit theorder, at which time the customer has committed to the order items andher credit card or bank account is charged. This type of workflowrequires many action steps before determining success or failure of thetask. A second type of workflow is where actions taken on one screen mayonly be verified for success or failure on another screen. For example,an appointment application allows you to create a new appointmentspecifying such items as an appointment name, location, date, time, andduration, among other possible pieces of information. But to determinewhether the entry is logged correctly often requires traversal to thecorrect month, day, and time of day to verify if the appointment isshowing correctly. The first type of workflow may be detected by lookingfor a combination of textual and navigational hints. For example, textlabels in the node match a dictionary of likely candidates (phone,address, and billing, among other possibilities.). Multiple text inputfields on the same screen. And navigational buttons or links labellednext, previous, continue, etc. Determining success or failure for theworkflow is reserved until there is a screen that denotes a completedflow, such as “order placed” or “reservation made.” The invention isprogrammed to successfully fully exercise this type of workflow usingstandard testing store front protocols and to identify and report anddeficiencies or deviations from expected results both catastrophic,where the application crashes or the process never successfullycompletes, and more subtle, where use of a back button or entry ofincomplete information on a screen results in order reset, double chargeor other failure states familiar to those skilled in the art which allowa user to progress in use of the mobile app but mildly to significantlydiminish the usability of the tool from the point of view of the user.The second type of workflow is detected from the context of creating anew item inside the mobile app, such as an appointment or new contact.Attributes from the create new item context are used to find the itemelsewhere in the application. For example, the date and time of anappointment or the name of a contact. Again, the invention includesprogramming to identify, traverse and exercise this second type ofworkflow as outlined directly above. Abnormal program ends, programprogress halts, and more subtle failures which may include failure totransfer schedule or other list data from an input screen to the correctreceiver fields either within the running mobile app or within anotherco-resident mobile app, among other defects known or likely to diminishuser experience are captured and analyzed.

Regardless of the testing mode that the system uses, test results arenormalized and interpreted within the test result analysis module 117.This module receives raw results from the bots working in any mode andanalyzes them for known success or failure indicators as well aspreviously uncharacterized deviation from expected UI interactivecomponent behavior. Analysis may make use of the analytic capabilitiesof the results based learning module 118 to predictively interpret thesignificance of unknown result data. Analyzed result data for a mobileapp may be permanently stored in the mobile application exercise resultdata store 131 for both later retrieval and review and possibly for useas a usability characteristic reference during testing of similar mobileapps. The raw bot generated data may also be stored in the data store131 for future re-analysis or review as new resources become available.Analyzed result data, raw bot data or both may also be transmitted to aclient's software engineering issue tracking system such as: JIRA™,BUGZILLA™, SLACK™, and VSO™ to name a subset of the trackers availableas normalized for transmission 134 to each of these services through thethird-party software engineering service normalizer 122. This allowsmobile app test results to serve as a part of the client's overallsoftware management schema rather than an isolated, add-on service thatmust then be manually integrated into client workflow. The utility ofthe intelligent mobile application testing system to software—softwareengineering issue tracking system communication channel is augmented inthat various aspects of the invention are designed to accept updatedmobile app code and testing directives from the client through thethird-party software engineering service normalizer 122 and will thenexercise the new mobile app revision for issues including reversions.Analysis results are passed on to a test progress recorder 119 toprovide clients with an indication of what screens have been tested andwhat is still left to complete as well as certain meaningful interimresults, if available. The system also uses test results analyzed usingpreprogrammed mobile app data metrics for a plurality of core functionsto provide clients with standalone usability statistics, statisticsindicating the mobile app's stability when subjected to specificchallenges and usability in comparison to other mobile apps in the samecategory among other statistics known useful to those skilled in the artbut not listed for brevity's sake 120. A client may get more detaileddescriptions of application abnormal ends, loss of responsivity issues,slow responsiveness, as well as subtler usability issues, possiblyincluding the program instructions that form the root cause that may bepresented in a client controllable video format that provides the exactmobile app screen status images with synchronized internal programinstructions and key variable values which may be finely controlled forboth playback location and playback speed through the services of theimprovement recommendations module 121 which will also, when appropriateand available, provide recommendations on how an issue may be resolved.All information produced by the test statistics module 120 andimprovement recommendations module 121 may be permanently saved in adata store record for the mobile app tested 131 as well as beingdirectly displayed to the client 134, 132.

FIG. 2 is a method flow diagram 200 of the function of the intelligentmobile application testing system according to one aspect. While somearrangements may run a test mobile app on a dedicated module which isintegral to the intelligent mobile application testing system 111, it isexpected that mobile apps will be tested on a plurality of the mobiledevices available from the plurality of manufacturers present at thetime of testing using the native operating system of those devices suchas but not necessarily limited to APPLE IOS™, GOOGLE ANDROID™, andMICROSOFT WINDOWS™ and under installation and execution control of theintelligent mobile application testing system through standardautomation APIs 201. Automated bots then crawl through the mobile appunder test such as using contextual hints that are part of the mobileapp's screen (also referred to as “node” herewithin) progression, typesof UI elements present on a screen and UI interactive element placementin that progression, among other hints known to those skilled in theart, and both previously learned mobile app traversal logic and explicithuman directives pertaining to the successful traversal of certain UIelements found in the current mobile app where specific information ofelement activation progression may be needed to simulate human likeinteractions for each element within the mobile app 202.

Responses to UI element exercise may be tested 203 againstpreprogrammed, learned or client provided expected results for thatelement to determine whether the element functions correctly. Unexpectedresults are recorded on a graphical representation of the mobile appgenerated by the intelligent mobile app test system along with otherdata pertaining to the current screen or node 211. Regardless of whetherunexpected behavior is found with an element, the intelligent mobile apptest system works to completely map each element's function and noderelationships for the entire mobile app 204 by activating each UIinteractive element present on each screen encountered 205. This mappingof a mobile app by the intelligent mobile application testing system mayoccur using four specialized test progression modes, although at anygiven instant of the test run, only one mode is active.

One such test mode is the discovery mode 113 which may be used primarilywhen the intelligent mobile application testing system encounters ascreen of the test mobile app of new or unknown functionality. When thatcondition is met, the bot assesses which UI components of the node mayreceive interactive user commands. For example, which components mayrespond to click or tap commands, which components may receive textinput and which component or components may respond to more complexgestures such as swipes, flicks or pinches, just to name a few of themany possible gestures available to a mobile app programmer. For eachscreen reference to each UI component, whether it responds directly orpossibly indirectly to some form of user interactive command, and itsposition on the screen is saved as part of the screen's noderepresentation internal to the intelligent mobile application testingsystem. The discovery mode assessment is partially done from standardautomation information, but standard information may be very limitedand, in some cases, may be entirely incorrect. Therefore, the inventionincludes heuristic programming algorithms that improve the accuracy ofdetermining what interaction commands are possible on the screen. Thisis generally based on such cues as the type of control(s) used toimplement the screen layout and content, and where on the screen tosimulate the interaction command although this list is not meant tolimit the types of interactions investigated by the invention. Forexample, sometimes a child control is reported to be unresponsive tointeraction commands but it has a parent or ancestor control that isregistered to respond to commands. Depending on the control types of theancestor and the parent, this may be a clue to not direct the command tothe ancestor control but to the child instead. The reason is based upona generally good guess that a child control has a higher z-order in theUI layout than the ancestor control. With a higher z-order, the childcontrol is on top of the ancestor. Therefore, scenarios where this isthe case are particularly searched for, and if so the command directedto the child control even though the child control is reported to beunresponsive. This works because the ancestor control acts as asurrogate, and eventually receives and processes the command as long asit originated from within the x & y coordinate boundaries of the childcontrol and no other dependent child control has an even higher z-orderthan the target control. Of course, the previous is just one of multiplepossible examples of how the heuristic programming embodied in theinvention may allow greater interactive feature investigation by betterreproducing the actions a human user may perform during use than by justrandomly activating interactive elements, but the example should in noway be interpreted to limit the invention to identifying and correctlytraversing similar UI construction methods. Next the bot must decidewhat action or actions should be taken in order to exercise this portionof the application and/or discover additional functionality further intothe application. This decision may be aided using both intra-mobile apppredictive analytics provided by any existing test results 117 and anylearning allowed by the synthesis of those results into predictiveinsight 118, and any previous data retrieved on similar mobile apps 131and made available to the system 116. Once a set of actions are thusdetermined, the bot makes an assessment regarding success or failureregarding the actions taken. In discovery mode, success is achieved ifeach of the following hold true: the application did not crash 208; theapplication did not throw any exceptions 206; the application did notpopup an error message to the UI 206; and, the screen has changed insome way regarding either control composition or content when comparedto the screen present before any actions were taken 207. Otherwise it isrecorded that an application failure has occurred because of activationof the tested interactive component which is saved as part of theelement's node in the mobile app's multidimensional graph representation211. Regardless of success or failure, the bot continues in discoverymode which means it tries to continue to explore the application forpathways that have not yet been traversed.

A second test mode which may be used by aspects of the invention iscrawler mode 114. Crawler mode is invoked when the bot is traversingthrough a mobile app, and arrives at points in a mobile app where“forward exploration” is no longer possible. Therefore, the bot needs togo back to a previously known node in the mobile app to explore otherareas of the mobile app that have not been explored or have been onlypartially explored. Such reverse traversal may be as simple as the goingto the previous screen using an available back button interactivecomponent, but in many cases traversal through nodes is not linear. So“going back” may not provide much utility. Also, some mobile apps do notsupport the “back” button at all. The system thus uses a statisticalweighting of all unexercised UI components under these circumstances.The system creates a ranking of the likelihood of how much functionalitysits behind each UI component to select a current node residentinteractive component with the highest probability of leading to apreviously mapped area of the mobile app. Once the target UI componentis chosen, then an application graph constructed by linking mobile appscreens together in a multidimensional graph represented relationship isused to determine the location of the test bot within the mobile appnode structure and the action steps needed to traverse known paths fromthe current node in the mobile app to a desired node where stillunexplored UI components may be accessed. Also, some paths within a testmobile app may be either transient or unidirectional, so the bot's firstattempt to determine the sequence of pathways may not always yield anexpected result. Therefore, the bot must recognize differences inapplication behavior from its expected behavior, update themultidimensional graph of mobile app nodes accordingly, and devise a newstrategy for navigating through the application to the desired node.This process repeats until the desired node is reached.

A third testing mode that may be used by aspects of the intelligentmobile application testing system, training mode 112, is invoked whenone or more nodes of the mobile app require specific text informationsuch as but not limited to a username, password, name of a particularobject or name of a person of geographical location; a specificactivation sequence of multiple interactive UI components of other setof actions specific to an individual or group known to those skilled inthe art. To traverse such specific types of interface elements wheretrial and error using random text entry or UI component activation willnot result in successful traversal of a screen of the mobile app, theclient may elect to teach the intelligent mobile application testingsystem the interaction information required using the client interface132, which is shown in this arrangement as being local to the testsystem for illustrative purposes, but may also be remote and connectedover an network including a vpn tunneled on the internet 134. In action,the bot may be explicitly trained for an exact set of actions on aparticular screen, if desired. The client may use the client interfaceportal 132 to identify the application screen on which it wants to trainthe bot by visually selecting UI control components one by one,specifying the correct action to be performed by the test system at thatcontrol and/or entering any specific value to populate into the controlin the cases of text responses. Each screen is a unique node in theapplication multi-dimensional graph. So the trained action and values iscreated under the graph point specified by the combination of the nodeidentifier plus the unique UI control component identifier. When the botis running and encounters a matching node and control(s), the trainedactions and values are used by the bot to traverse through that node ofthe application.

A last testing mode that may be used by various aspects of theintelligent mobile application testing system is a workflow mode 115.Two workflow types are modelled by the intelligent mobile applicationtesting system. One type involves a series of actions that span multiplescreens (nodes) to complete a task. A good example is the “check-out”process for a store front application. Typically, there are multiplescreens, one asking for shipping information, then one for billinginformation, one for confirmation of items in the shopping basket, andthen finally a screen to review an order a final time in its final formand submit the order, at which time the customer has committed to theorder items and her credit card or bank account is charged. This type ofworkflow requires many action steps before determining success orfailure of the task. A second type of workflow is where actions taken onone screen may only be verified for success or failure on anotherscreen. For example, an appointment application allows you to create anew appointment specifying such items as an appointment name, location,date, time, and duration, among other possible pieces of information.But to determine whether the entry is logged correctly often requirestraversal to the correct month, day, and time of day to verify if theappointment is showing correctly. The first type of workflow may bedetected by looking for a combination of textual and navigational hints.For example, text labels in the node match a dictionary of likelycandidates (phone, address, and

billing, among other possibilities.). Multiple text input fields on thesame screen. And navigational buttons or links labelled next, previous,continue, etc. Determining success or failure for the workflow isreserved until there is a screen that denotes a completed flow, such as“order placed” or “reservation made.” The invention is programmed tosuccessfully fully exercise this type of workflow using standard testingstore front protocols and to identify and report and deficiencies ordeviations from expected results both catastrophic, where theapplication crashes or the process never successfully completes, andmore subtle, where use of a back button or entry of incompleteinformation on a screen results in order reset, double charge or otherfailure states familiar to those skilled in the art which allow a userto progress in use of the mobile app but mildly to significantlydiminish the usability of the tool from the point of view of the user.The second type of workflow is detected from the context of creating anew item inside the mobile app, such as an appointment or new contact.Attributes from the create new item context are used to find the itemelsewhere in the application. For example, the date and time of anappointment or the name of a contact. Again, the invention includesprogramming to identify, traverse and exercise this second type ofworkflow as outlined directly above. Abnormal program ends, programprogress halts, and more subtle failures which may include failure totransfer schedule or other list data from an input screen to the correctreceiver fields either within the running mobile app or within anotherco-resident mobile app, among other defects known or likely to diminishuser experience are captured and analyzed 206.

During the course of analysis, it is possible that a mobile app mayabnormally end due to a catastrophic error 208. Under thesecircumstances, the intelligent mobile app testing system is designed tofirst recognize this condition and, as no further mapping and analysisof the mobile app would be possible in that state, restart the mobileapp 209 placing a bot on the last known active screen 210 and recordingboth the UI element's failure along with all available diagnosticinformation for the element on that screen's graph node 211 as well asinsuring that the defective element is avoided. The progression of fullymapped screens 212, 214 eventually will result in the full mapping ofthe mobile app 213 at which time the results may be presented in theclient 215, possibly in the form of statistics for stability,instantaneous and predicted resource usage on the host device of mobileapp functions, standalone usability, and comparative usability withother known mobile apps in the same category among other statisticsknown to those skilled in the art. Another form of presentation may be afinely controllable video representation of the bot's activities duringmobile app mapping including available machine state information ofselected interest to the client with the ability to zoom to areas ofunexpected programming behavior including program stops and abnormalends among other possible defects. These could then be reviewed “frameby frame” to allow troubleshooting of the issue. More extensive dumps ofmobile device memory may also be sent to the client's softwareengineering package 122 to aid in correction, if desired. All data mayalso be saved to a data store 131 for later review 216.

FIG. 3 is a flow diagram 300 of an exemplary function of the intelligentmobile application, testing system for mapping the navigationalrelationships between pages of a mobile application according to oneaspect. An important aspect of analyzing the function any mobile app isan accurate representation of the relationships between the mobile app'sscreens (which may also be referred to as “nodes” herein). Theintelligent mobile app testing system performs this mapping byactivating each UI interactive element on each screen starting with thefirst screen presented upon mobile app startup 301. This first screen isgiven the top node representation 310 in a multidimensional map that thesystem creates as it does its mapping. The resultant screen of a UIinteractive element 311, 312, 313, if screen navigation is the UIelement's action, is compared to all previously encountered pages 302and if the screen has not previously been encountered 304, a new node iscreated and added to the map 303 for the new screen 314, placed indimensional relationship to previously created nodes by contextual cluesencountered during previous mapping of mobile app and predictiveanalytic learning. Analysis of the UI elements on the new screen is thenbegun possibly employing contextual cues, explicit human directives forthat screen and prior predictive analytic learning which may include butis not limited to inferential statistics, linear regression, decisiontrees and data feedback loops to best mimic human interaction. New nodesare thus added until all screens of the mobile app are discovered andadded to the graph type mapping. Activation of an interactive UI elementmay also cause a bot, and therefore, by extension a human user to betaken to a previously encountered screen 304 for multiple mobile appdesign reasons. During mobile app testing, such an eventuality may causeonly a new link 321 (line darkened only for illustrative emphasis)between the source node and the target node to be created. If unanalyzedinteractive UI elements exist on the previously graphed landing node,the bot will then concentrate on characterizing one or more of thoseelements until taken to another mobile app screen 305. Multidimensionalgraphical mapping continues until all interactive UI elements have beenanalyzed and no further links are found present.

FIG. 4 is an illustration of an analysis summary screen 400 for a pageof a hypothetical mobile application produced as part of the function ofthe intelligent mobile application testing system as per one aspect. Tobe useful data resultant of any analysis is best presented in formatsthat are both intelligible to the recipient of that data and in suchways that the data may be quickly digested with the possibility ofexposing greater detail should the recipient desire. Shown here is onepossible static type display of data created by an aspect of theinvention of the plurality that may be created to summarize thefunctional status of a mobile app's UI elements 410, 415. Here, theclient may select the node, or screen of interest 405 a from themultidimensional graph representation created by the system (see FIG. 3)405. Node selection here brings up a display of the selected mobile appscreen 410 with its UI elements labeled for later reference (410A, 410B,410C, 410D, 410E, 410F) 415. The screen 410 is a simplifiedrepresentation of an item search and selection screen that may displayin the early-mid screen progression of a shopping app. UI element 410Amay show the available items for purchase once a merchandise category isselected elsewhere. The item to be displayed 410A being controlled byelements 410C which is to cause the display of the next item in themerchant's inventory offerings for the category and 410B which causesthe display of the previous item in the merchant's inventory offeringsfor the category, together meant to allow full access to availablecategory items. UI element 410D is meant to allow the mobile app user toadd an item of choice for purchase to a virtual shopping cart, displayedon another screen accessed by the activation of UI interactive element410F. The mobile app user may also return to the preceding screen 410E,for example to change merchandise categories once all desired selectionsin the current category are made, although other possible reasons forreturning to the previous page may exist.

Below the graphical representation 410 of the client selected node 405 ais a list type summary display of the results of intelligent mobile apptesting system analytical exercise of the mobile app screen chosen bythe client 415. The list includes a UI element's reference 415 a (A,401A) from the screen graphic representation panel 410, a shortdescription of the activity ascribed to the UI element by the testingsystem 415 a 1 and a brief descriptor of the test system's functionalfindings for that element 415 a 2, which for 415 a indicates that nofunctional issues were found. From the display, it may be quicklydetermined that most of the UI elements for node 311 405 a, 410 exhibitonly expected behaviors and are given a “Functional” designation. UIelement 410E, however is reported by the testing system to have had apossibly serious action programming defect as using the “Back” UIinteractive element to return designated previous page results in theloss of items already added to the cart 415 b. A client may then chooseto display more detailed information on the defect by activating an iconpresent next to the reported issue 415 c. The expanded detail may bedisplayed in manners such as but not limited to a pop-up window thatopens on the same testing system test result page as the summary, opensa new page to display the results interactively where multiple layers ofincreasing detail may be available, sending all pertinent detailinformation to the clients software engineer issue tracking system orother actions familiar to those skilled in the art for displaying orqueuing such information for action.

FIG. 5 is an example mobile application usability summary screen 500produced as part of the function of the intelligent mobile applicationtesting system according to one aspect. The system also uses informationsupplied by either previous mobile app test results or supplied fromother sources if available, to rate the usability of the current testmobile app. Usability summaries may be standalone usability ratingscalculated using metrics for the expected behaviors of standardinteractive UI elements that are present in the test mobile app, orcomparative usability against overall other mobile apps in the samemobile app category, merchant storefront apps being a non-exclusivecategory example. A comparative usability report display 510 may containa header stating the category chosen by the test system and which mayalso establish the rating range used 520. The current test mobile appscomparative usability score may then be given 525 followed by a list oftest system findings which contributed to the score. These factors mayoccasionally be positive if the mobile app author has used aparticularly effective, efficient or innovative method, perhapscombinations of all three characteristics, to accomplish a function ofthe mobile app (not shown) but will usually be a list of defects ofdeficiencies that could or need to be improved to better the mobile app530. In addition to the probable listing of items in need of correction,each item may provide a mechanism 535 by which the client may receivemore specific programming issues that may have led to the negativefinding as well as possible information on how to affect the correctivechange or changes to remedy each deficiency found. These data may bedisplayed by pop-up window on the same client display screen oractivation of the icon to display the advice information 535 may open adedicated window, possibly offering a hierarchy of correctiveinformation detail for the client to choose at their discretion. Theclient may also be given an option to send all pertinent intelligentmobile app testing system discovered programming, machine state andremediation advice text for one or more of the reported defects 530 totheir software engineer package for inclusion into the client's standardbug tracking policy.

Hardware Architecture

Generally, the techniques disclosed herein may be implemented onhardware or a combination of software and hardware. For example, theymay be implemented in an operating system kernel, in a separate userprocess, in a library package bound into network applications, on aspecially constructed machine, on an application-specific integratedcircuit (ASIC), or on a network interface card.

Software/hardware hybrid implementations of at least some of the aspectsdisclosed herein may be implemented on a programmable network-residentmachine (which should be understood to include intermittently connectednetwork-aware machines) selectively activated or reconfigured by acomputer program stored in memory. Such network devices may havemultiple network interfaces that may be configured or designed toutilize different types of network communication protocols. A generalarchitecture for some of these machines may be described herein in orderto illustrate one or more exemplary means by which a given unit offunctionality may be implemented. According to specific aspects, atleast some of the features or functionalities of the various aspectsdisclosed herein may be implemented on one or more general-purposecomputers associated with one or more networks, such as for example anend-user computer system, a client computer, a network server or otherserver system, a mobile computing device (e.g., tablet computing device,mobile phone, smartphone, laptop, or other appropriate computingdevice), a consumer electronic device, a music player, or any othersuitable electronic device, router, switch, or other suitable device, orany combination thereof. In at least some aspects, at least some of thefeatures or functionalities of the various aspects disclosed herein maybe implemented in one or more virtualized computing environments (e.g.,network computing clouds, virtual machines hosted on one or morephysical computing machines, or other appropriate virtual environments).

Referring now to FIG. 6, there is shown a block diagram depicting anexemplary computing device 10 suitable for implementing at least aportion of the features or functionalities disclosed herein. Computingdevice 10 may be, for example, any one of the computing machines listedin the previous paragraph, or indeed any other electronic device capableof executing software- or hardware-based instructions according to oneor more programs stored in memory. Computing device 10 may be configuredto communicate with a plurality of other computing devices, such asclients or servers, over communications networks such as a wide areanetwork a metropolitan area network, a local area network, a wirelessnetwork, the Internet, or any other network, using known protocols forsuch communication, whether wireless or wired.

In one aspect, computing device 10 includes one or more centralprocessing units (CPU) 12, one or more interfaces 15, and one or morebusses 14 (such as a peripheral component interconnect (PCI) bus). Whenacting under the control of appropriate software or firmware, CPU 12 maybe responsible for implementing specific functions associated with thefunctions of a specifically configured computing device or machine. Forexample, in at least one aspect, a computing device 10 may be configuredor designed to function as a server system utilizing CPU 12, localmemory 11 and/or remote memory 16, and interface(s) 15. In at least oneaspect, CPU 12 may be caused to perform one or more of the differenttypes of functions and/or operations under the control of softwaremodules or components, which for example, may include an operatingsystem and any appropriate applications software, drivers, and the like.

CPU 12 may include one or more processors 13 such as, for example, aprocessor from one of the Intel, ARM, Qualcomm, and AMD families ofmicroprocessors. In some aspects, processors 13 may include speciallydesigned hardware such as application-specific integrated circuits(ASICs), electrically erasable programmable read-only memories(EEPROMs), field-programmable gate arrays (FPGAs), and so forth, forcontrolling operations of computing device 10. In a particular aspect, alocal memory 11 (such as non-volatile random access memory (RAM) and/orread-only memory (ROM), including for example one or more levels ofcached memory) may also form part of CPU 12. However, there are manydifferent ways in which memory may be coupled to system 10. Memory 11may be used for a variety of purposes such as, for example, cachingand/or storing data, programming instructions, and the like. It shouldbe further appreciated that CPU 12 may be one of a variety ofsystem-on-a-chip (SOC) type hardware that may include additionalhardware such as memory or graphics processing chips, such as a QUALCOMMSNAPDRAGON™ or SAMSUNG EXYNOS™ CPU as are becoming increasingly commonin the art, such as for use in mobile devices or integrated devices.

As used herein, the term “processor” is not limited merely to thoseintegrated circuits referred to in the art as a processor, a mobileprocessor, or a microprocessor, but broadly refers to a microcontroller,a microcomputer, a programmable logic controller, anapplication-specific integrated circuit, and any other programmablecircuit.

In one aspect, interfaces 15 are provided as network interface cards(NICs). Generally, NICs control the sending and receiving of datapackets over a computer network; other types of interfaces 15 may forexample support other peripherals used with computing device 10. Amongthe interfaces that may be provided are Ethernet interfaces, frame relayinterfaces, cable interfaces, DSL interfaces, token ring interfaces,graphics interfaces, and the like. In addition, various types ofinterfaces may be provided such as, for example, universal serial bus(USB), Serial, Ethernet, FIREWIRE™, THUNDERBOLT™, PCI, parallel, radiofrequency (RF), BLUETOOTH™, near-field communications (e.g., usingnear-field magnetics), 802.11 (WiFi), frame relay, TCP/IP, ISDN, fastEthernet interfaces, Gigabit Ethernet interfaces, Serial ATA (SATA) orexternal SATA (ESATA) interfaces, high-definition multimedia interface(HDMI), digital visual interface (DVI), analog or digital audiointerfaces, asynchronous transfer mode (ATM) interfaces, high-speedserial interface (HSSI) interfaces, Point of Sale (POS) interfaces,fiber data distributed interfaces (FDDIs), and the like. Generally, suchinterfaces 15 may include physical ports appropriate for communicationwith appropriate media. In some cases, they may also include anindependent processor (such as a dedicated audio or video processor, asis common in the art for high-fidelity AN hardware interfaces) and, insome instances, volatile and/or non-volatile memory (e.g., RAM).

Although the system shown in FIG. 6 illustrates one specificarchitecture for a computing device 10 for implementing one or more ofthe aspects described herein, it is by no means the only devicearchitecture on which at least a portion of the features and techniquesdescribed herein may be implemented. For example, architectures havingone or any number of processors 13 may be used, and such processors 13may be present in a single device or distributed among any number ofdevices. In one aspect, a single processor 13 handles communications aswell as routing computations, while in other aspects a separatededicated communications processor may be provided. In various aspects,different types of features or functionalities may be implemented in asystem according to the aspect that includes a client device (such as atablet device or smartphone running client software) and server systems(such as a server system described in more detail below).

Regardless of network device configuration, the system of an aspect mayemploy one or more memories or memory modules (such as, for example,remote memory block 16 and local memory 11) configured to store data,program instructions for the general-purpose network operations, orother information relating to the functionality of the aspects describedherein (or any combinations of the above). Program instructions maycontrol execution of or comprise an operating system and/or one or moreapplications, for example. Memory 16 or memories 11, 16 may also beconfigured to store data structures, configuration data, encryptiondata, historical system operations information, or any other specific orgeneric non-program information described herein.

Because such information and program instructions may be employed toimplement one or more systems or methods described herein, at least somenetwork device aspects may include nontransitory machine-readablestorage media, which, for example, may be configured or designed tostore program instructions, state information, and the like forperforming various operations described herein. Examples of suchnontransitory machine-readable storage media include, but are notlimited to, magnetic media such as hard disks, floppy disks, andmagnetic tape; optical media such as CD-ROM disks; magneto-optical mediasuch as optical disks, and hardware devices that are speciallyconfigured to store and perform program instructions, such as read-onlymemory devices (ROM), flash memory (as is common in mobile devices andintegrated systems), solid state drives (SSD) and “hybrid SSD” storagedrives that may combine physical components of solid state and hard diskdrives in a single hardware device (as are becoming increasingly commonin the art with regard to personal computers), memristor memory, randomaccess memory (RAM), and the like. It should be appreciated that suchstorage means may be integral and non-removable (such as RAM hardwaremodules that may be soldered onto a motherboard or otherwise integratedinto an electronic device), or they may be removable such as swappableflash memory modules (such as “thumb drives” or other removable mediadesigned for rapidly exchanging physical storage devices),“hot-swappable” hard disk drives or solid state drives, removableoptical storage discs, or other such removable media, and that suchintegral and removable storage media may be utilized interchangeably.Examples of program instructions include both object code, such as maybe produced by a compiler, machine code, such as may be produced by anassembler or a linker, byte code, such as may be generated by forexample a JAVA™ compiler and may be executed using a Java virtualmachine or equivalent, or files containing higher level code that may beexecuted by the computer using an interpreter (for example, scriptswritten in Python, Perl, Ruby, Groovy, or any other scripting language).

In some aspects, systems may be implemented on a standalone computingsystem. Referring now to FIG. 7, there is shown a block diagramdepicting a typical exemplary architecture of one or more aspects orcomponents thereof on a standalone computing system. Computing device 20includes processors 21 that may run software that carry out one or morefunctions or applications of aspects, such as for example a clientapplication 24. Processors 21 may carry out computing instructions undercontrol of an operating system 22 such as, for example, a version ofMICROSOFT WINDOWS™ operating system, APPLE macOS™ or iOS™ operatingsystems, some variety of the Linux operating system, ANDROID™ operatingsystem, or the like. In many cases, one or more shared services 23 maybe operable in system 20, and may be useful for providing commonservices to client applications 24. Services 23 may for example beWINDOWS™ services, user-space common services in a Linux environment, orany other type of common service architecture used with operating system21. Input devices 28 may be of any type suitable for receiving userinput, including for example a keyboard, touchscreen, microphone (forexample, for voice input), mouse, touchpad, trackball, or anycombination thereof. Output devices 27 may be of any type suitable forproviding output to one or more users, whether remote or local to system20, and may include for example one or more screens for visual output,speakers, printers, or any combination thereof. Memory 25 may berandom-access memory having any structure and architecture known in theart, for use by processors 21, for example to run software. Storagedevices 26 may be any magnetic, optical, mechanical, memristor, orelectrical storage device for storage of data in digital form (such asthose described above, referring to FIG. 6). Examples of storage devices26 include flash memory, magnetic hard drive, CD-ROM, and/or the like.

In some aspects, systems may be implemented on a distributed computingnetwork, such as one having any number of clients and/or servers.Referring now to FIG. 8, there is shown a block diagram depicting anexemplary architecture 30 for implementing at least a portion of asystem according to one aspect on a distributed computing network.According to the aspect, any number of clients 33 may be provided. Eachclient 33 may run software for implementing client-side portions of asystem; clients may comprise a system 20 such as that illustrated inFIG. 7. In addition, any number of servers 32 may be provided forhandling requests received from one or more clients 33. Clients 33 andservers 32 may communicate with one another via one or more electronicnetworks 31, which may be in various aspects any of the Internet, a widearea network, a mobile telephony network (such as CDMA or GSM cellularnetworks), a wireless network (such as WiFi, WiMAX, LTE, and so forth),or a local area network (or indeed any network topology known in theart; the aspect does not prefer any one network topology over anyother). Networks 31 may be implemented using any known networkprotocols, including for example wired and/or wireless protocols.

In addition, in some aspects, servers 32 may call external services 37when needed to obtain additional information, or to refer to additionaldata concerning a particular call. Communications with external services37 may take place, for example, via one or more networks 31. In variousaspects, external services 37 may comprise web-enabled services orfunctionality related to or installed on the hardware device itself. Forexample, in one aspect where client applications 24 are implemented on asmartphone or other electronic device, client applications 24 may obtaininformation stored in a server system 32 in the cloud or on an externalservice 37 deployed on one or more of a particular enterprise's oruser's premises.

In some aspects, clients 33 or servers 32 (or both) may make use of oneor more specialized services or appliances that may be deployed locallyor remotely across one or more networks 31. For example, one or moredatabases 34 may be used or referred to by one or more aspects. Itshould be understood by one having ordinary skill in the art thatdatabases 34 may be arranged in a wide variety of architectures andusing a wide variety of data access and manipulation means. For example,in various aspects one or more databases 34 may comprise a relationaldatabase system using a structured query language (SQL), while othersmay comprise an alternative data storage technology such as thosereferred to in the art as “NoSQL” (for example, HADOOP CASSANDRA™,GOOGLE BIGTABLE™, and so forth). In some aspects, variant databasearchitectures such as column-oriented databases, in-memory databases,clustered databases, distributed databases, or even flat file datarepositories may be used according to the aspect. It will be appreciatedby one having ordinary skill in the art that any combination of known orfuture database technologies may be used as appropriate, unless aspecific database technology or a specific arrangement of components isspecified for a particular aspect described herein. Moreover, it shouldbe appreciated that the term “database” as used herein may refer to aphysical database machine, a cluster of machines acting as a singledatabase system, or a logical database within an overall databasemanagement system. Unless a specific meaning is specified for a givenuse of the term “database”, it should be construed to mean any of thesesenses of the word, all of which are understood as a plain meaning ofthe term “database” by those having ordinary skill in the art.

Similarly, some aspects may make use of one or more security systems 36and configuration systems 35. Security and configuration management arecommon information technology (IT) and web functions, and some amount ofeach are generally associated with any IT or web systems. It should beunderstood by one having ordinary skill in the art that anyconfiguration or security subsystems known in the art now or in thefuture may be used in conjunction with aspects without limitation,unless a specific security 36 or configuration system 35 or approach isspecifically required by the description of any specific aspect.

FIG. 9 shows an exemplary overview of a computer system 40 as may beused in any of the various locations throughout the system. It isexemplary of any computer that may execute code to process data. Variousmodifications and changes may be made to computer system 40 withoutdeparting from the broader scope of the system and method disclosedherein. Central processor unit (CPU) 41 is connected to bus 42, to whichbus is also connected memory 43, nonvolatile memory 44, display 47,input/output (I/O) unit 48, and network interface card (NIC) 53. I/Ounit 48 may, typically, be connected to keyboard 49, pointing device 50,hard disk 52, and real-time clock 51. NIC 53 connects to network 54,which may be the Internet or a local network, which local network may ormay not have connections to the Internet. Also shown as part of system40 is power supply unit 45 connected, in this example, to a mainalternating current (AC) supply 46. Not shown are batteries that couldbe present, and many other devices and modifications that are well knownbut are not applicable to the specific novel functions of the currentsystem and method disclosed herein. It should be appreciated that someor all components illustrated may be combined, such as in variousintegrated applications, for example Qualcomm or Samsungsystem-on-a-chip (SOC) devices, or whenever it may be appropriate tocombine multiple capabilities or functions into a single hardware device(for instance, in mobile devices such as smartphones, video gameconsoles, in-vehicle computer systems such as navigation or multimediasystems in automobiles, or other integrated hardware devices).

In various aspects, functionality for implementing systems or methods ofvarious aspects may be distributed among any number of client and/orserver components. For example, various software modules may beimplemented for performing various functions in connection with thesystem of any particular aspect, and such modules may be variouslyimplemented to run on server and/or client components.

The skilled person will be aware of a range of possible modifications ofthe various aspects described above. Accordingly, the present inventionis defined by the claims and their equivalents.

What is claimed is:
 1. A system for automated intelligent mobileapplication testing comprising: a mobile application testing modulestored in a memory of and operating on a processor of a computing deviceand configured to: receive a mobile application for testing from anexternal source; communicate with a mobile device via a plurality ofstandard application programming interfaces; direct an operating systemof the mobile device to install the mobile application; identify andexercise each of a plurality of user interface elements on each of aplurality of screens presented by the mobile application, analyzingcontextual clues present in the plurality of user interface elements topredict correct behavior of that element while simulating humaninteraction with those elements; create a relationship representation ofa plurality of screens presented by the mobile application; identify anydeviation in behavior of any user interface elements tested frompredictively expected behavior for that element; communicate with anissue tracking system; and a test results output module stored in amemory of and operating on a processor of a computing device andconfigured to: format a plurality of results received from the mobileapplication testing module to best accomplish a predetermined functionof those results.
 2. The system of claim 1, wherein the predictiveanalysis is based at least in part on a plurality of previously-learnedbehavioral expectations.
 3. The system of claim 1, wherein thepredictive analysis is based at least in part on a plurality ofinstructions received from the issue tracking system.
 4. The system ofclaim 1, wherein at least one of the test result output module formatsis a user interface element behavior summary report for elements of themobile application.
 5. The system of claim 1, wherein at least one ofthe test result output module formats is a detailed program and machinestate report configured for presentation to a user for review.
 6. Thesystem of claim 1, wherein at least one of the test result output moduleformats is a report that provides metric derived usability scores andadvice on remedy choices.
 7. The system of claim 1, wherein at least oneof the test result output module formats is transmitted to the issuetracking system.
 8. The system of claim 1, wherein at least onerelationship representation of a plurality of screens of the mobileapplication is in the form of a multidimensional graph.
 9. A method forautomated intelligent mobile application testing comprising the stepsof: a) retrieving a mobile application to be tested from an externalsource using a mobile application testing module stored in a memory ofand operating on a processor of a computing device; b) directing, usinga plurality of application programming interfaces, the operating systemof a mobile device to install and run the mobile application; c)identifying and exercising each of a plurality of user interfaceelements on each of a plurality of screens presented by the mobileapplication, analyzing contextual clues present in the plurality of userinterface elements to predict correct behavior correct behavior of thatelement while simulating human interaction with those elements; d)creating a relationship representation of a plurality of screenspresented by the mobile application; e) identifying any deviation inbehavior of any user interface elements tested from predictivelyexpected behavior for that element; f) communicating with an issuetracking system; and g) formatting a plurality of results received fromthe mobile application testing module to best accomplish a predeterminedfunction of those results using a test results output module stored in amemory of and operating on a processor of a computing device.
 10. Themethod of claim 9, wherein the predictive analysis is based at least inpart on a plurality of previously-learned behavioral expectations. 11.The method of claim 9, wherein the predictive analysis is based at leastin part on a plurality of instructions received from the issue trackingsystem.
 12. The method of claim 9, wherein at least one of the testresult output module formats is a user interface element behaviorsummary report for elements of the mobile application.
 13. The method ofclaim 9, wherein at least one of the test result output module formatsis a detailed program and machine state report configured forpresentation to a user for review.
 14. The method of claim 9, wherein atleast one of the test result output module formats is a report thatprovides metric derived usability scores and advice on remedy choices.15. The method of claim 9, wherein at least one of the test resultoutput module formats is transmitted to the issue tracking system. 16.The method of claim 9, wherein at least one relationship representationof a plurality of screens of the mobile application is in the form of amultidimensional graph.